A Prototype-Based Semisupervised Learning Method for Few-Shot SAR Target Recognition

Deep learning-based methods have achieved extraordinary success in SAR automatic target recognition. However, deep learning conventionally necessitates a substantial number of labeled samples to achieve effective training, and labeled samples of new classes in real-world scenarios are scarce, which...

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Hlavní autoři:	Ruikang Hu, Xu Lan, Ye Li, Haiyan Zhu, Li Liu, Jingyuan Xia
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2026-01-01
Edice:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Témata:	Few-shot learning (FSL) synthetic aperture radar (SAR) automatic target recognition semisupervised learning
On-line přístup:	https://ieeexplore.ieee.org/document/11298499/
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